{"id":"W1992963734","doi":"10.1109/reconfig.2013.6732303","title":"Leakage power reduction in FPGA DSP circuits through algorithmic noise tolerance","year":2013,"lang":"en","type":"article","venue":"","topic":"Low-power high-performance VLSI design","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Field-programmable gate array; Computer science; Digital signal processing; Embedded system; Electronic engineering; Electronic circuit; Logic gate; Leakage (economics); Noise (video); Low-power electronics; Power (physics); Computer hardware; Engineering; Electrical engineering; Power consumption; Algorithm","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0001050823,0.000239713,0.0002285019,0.0001329087,0.0000431332,0.00006434078,0.0002093777,0.0001385234,0.001232186],"category_scores_gemma":[0.000008239456,0.0002324362,0.00004895923,0.0004407588,0.00003771302,0.001324496,0.00002249942,0.0002773714,0.002322558],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001691304,"about_ca_system_score_gemma":0.00001723538,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001838198,"about_ca_topic_score_gemma":0.00001091848,"domain_scores_codex":[0.998688,0.00001974806,0.0003350928,0.0002786488,0.0002064108,0.0004720899],"domain_scores_gemma":[0.9994624,0.00001735078,0.00002671117,0.0003789535,0.00004649813,0.00006803685],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00001545395,0.00034968,0.002202549,0.0003809522,0.0001370069,0.00006522451,0.01162036,0.1577727,0.6125443,0.001548808,0.1224008,0.09096213],"study_design_scores_gemma":[0.004386137,0.000346981,0.08238854,0.0004544037,0.0000407582,0.0002349089,0.001610208,0.2579013,0.6103908,0.00270945,0.03586238,0.003674098],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9280429,0.000440448,0.01572878,0.0001667786,0.001807044,0.0006579306,0.000002586589,0.0008318868,0.05232167],"genre_scores_gemma":[0.9957584,0.0001114759,0.002225925,0.00008610764,0.0001631657,0.000122118,0.000004837842,0.0000629354,0.001465012],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1001286,"threshold_uncertainty_score":0.9996808,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0079281373993649,"score_gpt":0.1951037445409861,"score_spread":0.1871756071416212,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}